1. Track Finding based on a Cellular Automaton Ivan Kisel Kirchhoff-Institut für Physik, Uni-Heidelberg Tracking Week, GSI January 24-25, 2005 KIP

2. 24-25 January 2005, GSIIvan Kisel, KIP, Uni-Heidelberg2 Level-1 Base Reconstruction Software STS Data CA Track Finder KF Track Fit PV Finder KF PV GeoFit KF SV GeoFit KF SV ConstrFit Performance Select/DiscardEvent TRD Data CA Track Finder KF Track Fit RICH Data EN Ring Finder Track Merger KF Track Fit L1/FPGA L1/CPU HLT HLT

3. 24-25 January 2005, GSIIvan Kisel, KIP, Uni-Heidelberg3 Cellular Automaton Method  Being essentially local and parallel cellular automata avoid exhaustive combinatorial searches, even when implemented on conventional computers..  Since cellular automata operate with highly structured information (for instance sets of tracklets connecting space points), the amount of data to be processed in the course of the track search is significantly reduced. -  Further reduction of information to be processed is achieved by smart definition of the tracklets neighborhood.  Usually cellular automata employ a very simple track model which leads to utmost computational simplicity and a fast algorithm.. 6 543 2 1 Define :. CELLS -> TRACKLETSCELLS -> TRACKLETS NEIGHBORS -> TRACK MODELNEIGHBORS -> TRACK MODEL RULES -> BEST TRACK CANDIDATERULES -> BEST TRACK CANDIDATE EVOLUTION -> CONSECUTIVE OR PARALLELEVOLUTION -> CONSECUTIVE OR PARALLEL Define :. CELLS -> TRACKLETSCELLS -> TRACKLETS NEIGHBORS -> TRACK MODELNEIGHBORS -> TRACK MODEL RULES -> BEST TRACK CANDIDATERULES -> BEST TRACK CANDIDATE EVOLUTION -> CONSECUTIVE OR PARALLELEVOLUTION -> CONSECUTIVE OR PARALLEL Collect tracksCreate tracklets

4. 24-25 January 2005, GSIIvan Kisel, KIP, Uni-Heidelberg4 CA Track Finding in STS MC Truth -> YES PERFORMANCE Evaluation of efficiencies Evaluation of resolutions Histogramming Timing Statistics Event display MC Truth -> NO RECONSTRUCTION Fetch MC data Copy to local arrays and sort Create tracklets Link tracklets Create track candidates Select tracks Main Program Event Loop Reconstruction Part Performance Part Parabola Straight line

5. 24-25 January 2005, GSIIvan Kisel, KIP, Uni-Heidelberg5 CA Track Finding Efficiency in STS and TRD ALL MC TRACKS RECONSTRUCTABLE TRACKS Number of hits >= 3 REFERENCE TRACKS Momentum > 1 GeV

6. 24-25 January 2005, GSIIvan Kisel, KIP, Uni-Heidelberg6 CA Track Finding – Future Plans Modify according to the STS and TRD design choices Improve the track model Investigate efficiency of D0 secondary tracks Increase speed